For the stress-induced anisotropy, Hiramatsu et al. (2010) showed that the normalized time delay by path length is proportional to the differential strain rate obtained by GPS observations and estimated a spatial variation in the stressing rate of 3 kPa/year in the upper crust in and around the high strain rate zone.
A similar trend was found with respect to the passaged chondrocytes embedded in the CL gels by estimating the spatial morphology in terms of sphericity (Sc) determined 4 days after seeding.
For this purpose the methodology developed can be used for time series data by estimating inventory-specific spatial trends or, in the case of a number of inventories, by integrating a space-time effect (Augustin et al. [2009]).
Hence, the spatial effect has been modeled in two ways as discussed earlier by estimating spatial lag as well as error model (Tables 2 and 3).
Several authors have proposed techniques that delineate patches by estimating spatial gradients of labeling, either from photomicrographs (Amir et al. 1993; Malach et al. 1993, 1994; Tanigawa et al. 2005) or from reconstructions of labeled somata (Lübke and Albus 1992).
Only for figure illustrations from single seed correlation analyses, data were spatially filtered using a Gaussian filter to a maximum smoothness of 4 mm full-width at half-max (FWHM) (by estimating the FWHM before spatial filtering), ensuring uniformity across the surface and maintaining spatial specificity while increasing the signal-to-noise ratio (SNR) (Chung et al., 2005).
An individual tree canopy (ITC) method based on aerial LiDAR has been developed to assess forest structure by estimating the density and spatial configuration of trees in four different height classes.
A volumetric spatial image of brain activity is created by estimating such an index of neuronal activity sequentially.
For example, pattern-classification algorithms have been built that will classify spatial patterns of fMRI data (2D images or 3D volumes) by estimating what task a subject was undertaking when each particular fMRI pattern was measured.
Target sample sizes were determined by roughly estimating the spatial area of a putative chimpanzee community home range, based on direct and indirect evidence of chimpanzee presence, then multiplying by the previously estimated density of chimpanzees in the Bulindi study community within the corridor region (0.66 chimpanzees per km [ 55]).
